Many display systems use digital image data to represent the image that is to be created. The digital data undergoes many processing steps to render each image and to prepare the image for display. For example, the image data is often scaled to change the resolution of the input image to that of the display modulator. Likewise, the intensity of the image may be altered to compensate for the type of modulator being used. For example, digital micromirror device (DMD™)-based displays must remove the gamma compensation that was added to the image data to facilitate display on a standard cathode ray tube display. The processing may alter the color space of the image stream to change the appearance of the projected image.
All of these image processing steps can increase the image data word size. Unfortunately, the image data word size of the display is often limited. For example, DMD-based displays use pulse width modulation to provide the appearance of gray scale images while using a binary light valve. Pulse width modulation requires a display frame period to be divided into a number of time slices equal to the number of possible gray levels. As the number of image data bits increases, the time slice representing the least significant bit slice becomes shorter than the response time of the modulator. Furthermore, increasing the number of bits increases the rate at which data must be loaded into the modulator. Due to either one of these factors, the image data word size must be limited, typically by truncating the image data word.
Truncating the image data word limits data rate into the modulator and limits the number of time slices that must be created each image frame. The truncation operation, however, necessarily creates quantization error which results in image artifacts. These artifacts, called false contours, appear as contours in the image that were not represented in the input image data.
Error diffusion methods have been developed to reduce the contouring effects of quantization errors. These error diffusion methods generally add the quantization error to surrounding pixels. Since the image data is generally processing in raster-scan format—from row-by-row from right to left and top to bottom—the pixels above and to the left of the pixel being processed have already been processed and the flow of the error signal is limited to the right and down.
New display processors process data for more than one pixel at a time. When several pixels are processed simultaneously, the standard down and to the right error flow cannot be implemented. What is needed is a new error diffusion method that is suitable for use in display systems that process multiple pixels simultaneously.